1. Introduction. 2. Objectives of the program. 3. Expected Graduate Attributes

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1. Introduction

Every life form, beginning from microscopic bacteria to multicellular organisms, can be considered as a system that has been perfected over millennia by Evolution. Beginning from thermodynamically efficient cellular processes to the molecular motors driving the bacterial flagella, each product of evolution is an optimized engineering design that can be translated into real-life applications across disciplines. Today’s interdisciplinary biology is well complemented by engineering domains including electronics, computer science, mechanics, and materials engineering. Computational biology, for example, permits solving biology problems using statistical, artificial intelligence and machine learning approaches. Extensive use of computational biology is essential in data-driven approaches including Genomics, Proteomics, Transcriptomics, and Metabolomics. This amalgamation of biology and computer science has transformed the landscape of the infectious and non-infectious diseases research allowing the development of new diagnostic and therapeutic modalities. Today’s disease diagnosis is much more specific and sensitive, thanks to biosensors, which have far-reaching applications not only in healthcare but also in the environment, energy, and agriculture. Some applications include in-situ biosensors for human biochemical parameters, environmental contaminants, soil moisture, soil physicochemical parameters, etc. Advances in Biology have not only permitted the early diagnosis of disease but have also contributed abundantly to therapeutic interventions. It is now possible to intervene in diseases taking a multi-pronged approach, including the development of new drugs; production of recombinant therapeutics; development of implantable sensors, control systems; and editing genetic defects. Similarly, synthetic biology and genome editing tools have enabled the development of industrially important organisms for biofuel production as well as environmental remediation. Together, these technologies have significantly contributed to extending the healthy lifespan of the human race and have shown promise towards food, water, and energy security. In other words, bioengineering as a discipline has evolved to a great extent in last couple of decades and now demands a different intellectual outlook and scientific understanding for its further study. Therefore, an undergraduate academic program in Bioengineering should reflect this rapid evolution of the discipline, underlying scientific and technological advancements and interdisciplinary cross talk so as to capture the mind of the next generation.

The Indian Institute of Technology Jodhpur is committed to achieving excellence in shaping the young minds of tomorrow with a unique blend of teaching techniques and hands-on research-based learning. The Institute works towards the holistic development of students allowing them to be able to assume leadership positions in Industry, Academia, and Entrepreneurial ventures. The Department of Bioscience & Bioengineering is committed to this goal and has developed academic programs that are interdisciplinary in nature and include a substantial component of courses from other science and engineering Departments. The Department aspires to produce Graduates, who can develop solutions to tackle local and global problems related to healthcare, energy, environment, water, and food.

2. Objectives of the program

The B. Tech. program in Bioengineering at IIT Jodhpur aims to equip our graduates with in-depth knowledge and hands-on training in areas that will be relevant for the next decade. The curriculum aims to impart knowledge and skills to budding engineers to address future challenges. This includes innovative pedagogy and highly interdisciplinary approach towards problem-solving.

The key objectives of this program are:

1. To provide a strong foundational understanding of concepts in biology, engineering, mathematics, and allied sciences, enabling students to approach bioengineering problems through interdisciplinary lenses.

2. To stimulate the development of disruptive technologies and futuristic research in the domains of healthcare, energy, and the environment

3. Expected Graduate Attributes

1. Graduates of the B. Tech program in Bioengineering will:

2. be able to choose, design, develop, and implement engineering solutions to solve technical problems in bioscience and bioengineering using trans-disciplinary knowledge and skill set.

3. be able to think out-of- the box to solve critical challenges and be able to innovate novel technologies for affordable healthcare, clean energy, sustainable agriculture, and safe environment.

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4. be able to work effectively as a member and leader in a multi-disciplinary team. 5. have the requisite skills and knowledge to be bio-entrepreneurs.

6. be able to effectively communicate biological/ bioengineering problems and solutions within the professional sphere and with the society at large.

7. be committed to high ethical standards in professional and social practices.

4. Learning Outcomes

1. Graduates of the B. Tech program in Bioengineering:

2. Will have comprehensive understanding of the essential concepts of bioscience and bioengineering encompassing cell and molecular biology, physiology, immunology, microbiology, genetics, genetic engineering, multi-omics, computational and systems biology.

3. Will gain trans-disciplinary knowledge and skill sets pertaining to biosensors, bioimaging, biomedical device development, biomaterials engineering and drug discovery.

4. Will be able to design, develop and implement technological solutions related to affordable healthcare, clean energy, sustainable agriculture and safe environment adopting a trans-disciplinary approach.

5. Will gain a strong understanding of the fundamentals of basic science, engineering, designing, computing and will get hands-on training on cutting edge technologies.

6. Will be able to apply the knowledge of artificial intelligence and machine learning in solving complex biological problems.

7. Will learn to think critically to solve complex problems pertaining to bioscience and bioengineering. 8. Will develop communication skills (verbal and written) to communicate effectively in the professional and

social sphere.

9. Will be committed to high ethical standards.

10. Will gain the knowledge and skills required to be an innovator-entrepreneur.

5. New skillsets targeted

Ability to:

1. Design and develop AI-based technologies in healthcare, environment, and agriculture. 2. Analyze spatial complexity of living systems using imaging and image processing.

3. Analyze and solve complex problems in the diverse fields of bioscience and bioengineering using omics and systems biology.

4. Integrate multidisciplinary technologies for the development of lab-on-chip devices, biosensors, and other smart devices.

5. Integrate omics data to quantitative structure-activity relationship for drug discovery and development 6. Design and develop smart biomaterials using micro- and nano-scale technologies

7. Design novel strategies for tissue engineering application 8. Design new therapeutic molecule in silico.

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6. Topic clouds and Mapping of Topic clouds with proposed courses

Table 1 Topics and Mapping of Topic with Courses

Area Topics Category (Core/

Techniques Technology/Systems)

Course (IE/IS/PC/PE)

Omics

•

Cells and organelles

•

Replication

•

Transcription and translation

•

Cell cycle

Core and Techniques Concepts & Dynamics: Molecular Cell Biology (PC 4th₎

Pre/Co-Req:

Biochemistry (PC 3rd₎

•

DNA, RNA, Proteins,

metabolites

•

Metabolic pathways

•

Biochemical analysis

•

Enzymes

Core and Techniques Biochemistry (PC 3rd₎

Pre/Co-Req: None

•

Inheritance

•

Polymerase chain reaction

•

Gene therapy

Core, Techniques and

Systems Genetics & Gene Manipulation (PC 5th₎

Pre/Co-Req: None

•

Genomics

•

Transcriptomics

•

Proteomics

•

Metabolomics

•

Mass Spectroscopy

Core and Techniques Introductory Omics (PC 6th₎

Pre/Co-Req: Concepts

& Dynamics:

Molecular Cell Biology (PC 4th₎

•

Microbial communities

•

Metagenome library

•

Metagenome sequencing

Core and Techniques Microbiomes and Metagenomics (PE)

Pre/Co-Req:

Microbiology (PC 3rd₎

•

Biological networks and

pathways

•

Data modeling

•

Multi-omics integration

Systems Computational

methods for multi-omics (PE)

Pre/Co-Req:Introductory

Omics (PC 6th₎

•

Omics analysis algorithms

•

DNA microarray

•

Data normalization

•

Data visualization

Core, Techniques and Systems

Microarray data analysis (PE)

Pre/Co-Req: None

•

Neural network

•

Deep learning models

•

Deep generative models

•

Representation learning

Systems Deep Learning (PC

6th₎ (From CS) Pre/Co-Req: Introduction to machine Learning (PC 3rd₎ Biomaterials

Engineering

•

Biodegradability Biocompatibility and

•

Biomaterial characterization

•

Implants

Biomaterials

Engineering (PC 6th₎

•

Cell adhesion on substrate

•

Biofilm formation

•

Surface modification

Core and Techniques Cell-material Interactions (PE)

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Pre/Co-Req:

Biomaterials

Engineering (PC 6th₎

•

Tissue repair and regeneration

•

Scaffolds

•

Animal cell culture

Core, Techniques and Systems Tissue Engineering (PE) Pre/Co-Req: Biomaterials Engineering (PC 6th_); Cell-Material Interactions (PE)

•

Sustained, on-demand and

targeted delivery

•

Drug loading and drug release

•

Pharmacokinetics and

pharmacodynamics

Systems Therapeutic delivery systems (PE)

Pre/Co-Req: Biomaterials Engineering (PC 6th₎

•

Human locomotion

•

Tissue mechanics

•

Viscoelasticity Core Principles of Biomechanics (PE) (From ME) Pre/Co-Req: Biomaterials Engineering (PC 6th₎

•

3D printing

•

Field deposition model (FDM)

•

Selective laser sintering

•

Stereo lithography Techniques and Systems Additive manufacturing (PE) (From ME) Pre/Co-Req: Biomaterials Engineering (PC 6th₎

•

Bio-transport

•

Hemodynamics

•

Momentum conservation

•

Bio-rheology

Core and Systems Bio-transport phenomena (PE) (From BSBE, CHE, ME) Pre/Co-Req: None Computational & Systems Biology • Bioinformatics • Bio computation • Mathematical modelling

Core and Techniques Computational and System Biology (PC 5th₎

Pre/Co-Req: Concepts

& Dynamics:

Molecular Cell Biology (PC 4th₎

• Numerical Methods for PDE • Ordinary Differential Equations

Core and Techniques Mathematical Biology (PE) (From MA)

Pre/Co-Req:

Computational Biology (PC 5th₎

•

Methods and method

development in computational biology

Core, Techniques and Systems Algorithms in biology (PE) Pre/Co-Req: None

•

Biosystems

•

Boundary conditions

Core and Techniques Modelling biological systems (PE)

Pre/Co-Req: None

•

Experiment design

•

validation

Core Design of experiments

(PE)(From MA)

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Bioimaging

•

Optical microscopy

•

Fluorescence microscopy

•

Digital imaging

•

Medical imaging

Systems Bioimaging (PC 6

th₎ (From CS/EE)

•

Fourier transform theory

•

Filtering

•

Image enhancement

Techniques and Systems

Digital Image

processing (PE) (From CS/EE) Pre/Co-Req: Bioimaging (PC 6th₎

•

Image reconstruction

•

Image restoration

•

Deep learning

•

2D, 3D registration Techniques and Systems Bio-image computing (PE) (From CS) Pre/Co-Req: Bioimaging (PC 6th₎

•

Electron scattering and diffraction

•

Scanning and transmission

•

Immuno and cryo-electron microscopy

Electron microscopy for biology (PE) (From CY)

Pre/Co-Req:

Bioimaging (PC 6th₎

Biosensors

•

Impedimetric, voltammetric, amperometric, electrical, optical sensors

•

Selectivity and sensitivity

Biosensors (PC 5th₎ (From EE)

Pre/Co-Req:

Biochemistry (PC 3rd₎

•

Genetic circuits for

biosensors

•

RNA based sensors

•

Reporter genes

Whole cell based biosensors (PE) Pre/Co-Req: Biosensors (PC 5th₎

•

Lithography

•

Micromachining

•

MEMS Techniques and

Systems Microsystems Fabrication

Technology (PE)(From EE)

•

Aptamer sensor

•

Cation-selective sensor

•

Dendrimer based sensor

Techniques and

Systems Chemosensors (PE) (From CY) Pre/Co-Req: Biosensors (PC 5th₎ Microbial systems for sustainable development

•

Microbial phylogeny

•

Metabolism

•

Microbial growth

•

Applied microbiology

Core and Systems Microbiology (PC 3rd₎

• Wastewater treatment • Bio-geo chemical cycling • Solid waste management • In situ and ex situ bioremediation

Systems Microbial remediation and Environmental Biotechnology (PE)

Pre/Co-Req:

Microbiology (PC 3rd₎

• Probiotic, symbiotic, plant – microbe interaction

• Fortified food

• Nutritional supplements • Single cell protein

Systems Microbes in food and sustainable agriculture (PE)

Pre/Co-Req:

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• Solid , liquid, gaseous biofuels

• Engineering microbes for biofuel production

• Different generations of biofuels and sustainability analysis

Systems Bioenergy (PE)

Pre/Co-Req: Microbiology (PC 3rd₎ Drug design and Development

•

Protein-protein interaction

•

Protein crystallography

•

Protein folding

Core and Techniques Biophysics and Structural Biology (PC 6th₎ Pre/Co-Req: Biochemistry (PC 3rd₎

•

Drug targets

•

Computer-aided drug design

•

Virtual screening

Core, Techniques and Systems Principles of Drug discovery (PE) Pre/Co-Req: Biophysics and Structural Biology (PC 5th₎ Biochemistry (PC 3rd₎

•

Pharmacophore

•

Drug metabolism

•

Chiral drug molecule

•

Antibiotics and antiviral

Core and Techniques Medicinal chemistry (PE) (CY)

Pre/Co-Req: None

•

Virus life cycle

•

Viral immunity

•

Antiviral drugs

Systems Viral infection and antiviral drug development (PE)

Fundamental

courses

•

Innate immunity Inflammatory response

•

Cell signaling

•

B- and T-cell lymphocytes

•

Clinical immunology

Core and Techniques The Human Immune System: Mechanisms to Detect, Defend and Attack (PC 4th₎ Pre/Co-Req: None

•

Membrane transportation

•

Muscle mechanics

•

Membrane potential

•

Cardiovascular, pulmonary, renal physiology

Core The Human Machine

for Engineers: Quantitative Physiology (PC 5th₎

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7. Course Categories, credit distribution and Credit Structure of B. Tech Programmes

Table 2 Proposed Course Categories and credit distribution in the proposed B. Tech Programmes

S.N. Course Type Course Category Regular

B.Tech. Double B.Tech. Credit Tota

l Credit Total

1 Institute Core (I) Engineering (IE) 34 69 34 59

Science (IS) 16 16

Humanities (IH) 12 9

2 Programme Linked (L) Science (LS) 7 0

3 Programme Core (P) Programme Compulsory (PC) 50 71 50 71

Programme Electives (PE) 18 18

B.Tech. Project (PP) 3 3

4 Open (O) Open Electives (OE) 10 10 0 0

5 Engineering Science (E)

Engineering Science Core (EC) 0 0 22 22

Engineering Science Elective (EE) 0 0 8 8

Total Graded 150 160

6 Non-Graded (N) Humanities (NH) 6 15 6 15

Engineering (NE) 3 3

Design/Practical Experience (ND) 6 6

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8. Credit Structure of B. Tech Programmes

Table 4 Credit Structure for B. Tech Programmes (Up 6000 Level)

Type L-T-P Distribution of contact and beyond contact hours Total Credits (TC=TH/3) Contact Hours

(CH) Beyond Contact Hours (BCH) Total Hours (TH)

1 hour of Lecture 1-0-0 1 hr 2 hr 3 hr 1

1 hour of Tutorial 0-1-0 1 hr 2 hr 3hr 1

1 hour of Lab/Project 0-0-1 1 hr 0.5 hr 1.5 hr 0.5

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9. List of Programme Compulsory Courses

Table 5 Programme Compulsory Courses

S. No Course Name Semester L-T-P Contact

Hours Credit

1 Biochemistry III 3-0-0 3 3

2 Microbiology III 3-0-2 5 4

3 Data Structures and Algorithms IV 3-0-2 5 4

4 Concepts and Dynamics: Molecular Cell Biology

IV 2-0-2 4 3

5 The Human Immune System: Mechanisms

to detect, defend and Attack IV 3-0-0 3 3

6 Biochemistry Laboratory IV 0-0-2 2 1

7 Computational and Systems Biology V 3-0-2 5 4

8 The Human Machine for Engineers: Quantitative Physiology

V 3-0-0 3 3

9 Biophysics and Structural Biology VI 3-0-1 4 3.5

10 Genetics and Gene manipulation V 3-0-2 5 4

11 Biosensors V 3-0-2 5 4 12 Bioimaging VI 3-0-0 3 3 13 Introductory Omics VI 3-0-0 3 3 14 Biomaterials Engineering VI 3-0-0 3 3 15 Deep Learning VI 3-0-3 6 4.5 Total 50

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10. Area-wise Programme Elective Courses

Table 6 Stream-wise Programme Electives Courses

S. No. Stream Courses L-T-P Credit

1 Omics

-

Microbiomes and metagenomics (level 4)

-

Computational methods for multi-omics (level 4)

-

Microarray data analysis (level 4)

3-0-0 3-0-2 3-0-0 3 4 3 2 Biomaterials

Engineering

-

Cell-material interactions (level 4) Tissue engineering (level 4)

-

Therapeutic delivery systems (level 4)

-

Principles of biomechanics (level 4; from ME)

-

Additive manufacturing (level 7; from ME)

-

Bio-transport phenomena 3-0-0 3-0-0 3-0-0 3-0-0 3-0-0 3-0-0 3 3 3 3 3 3 3 Computationa l and Systems Biology

-

Mathematical biology (level 4; from MA)

-

Algorithms in biology (level 4)

-

Modelling of biological systems (level 4)

-

Design of experiments (level 4; from MA)

3-0-0 3-0-0 2-0-2 3-0-0 3 3 3 3 4 Bioimaging

-

Electron microscopy for biology (level 4/6; from

CY)

-

Special topics on biomedical imaging (level 4)

-

Digital Image processing (level 4; from CS)

-

Bio-image computing (level 7; CS)

3-0-0 3-0-0 3-0-0 3 3 3

5 Biosensors

-

Whole cell based biosensors (level 4)

-

Special topics in biosensors (level 4)

-

Microsystems fabrication technology (level 7; from EE)

-

Chemosensors (level 6; from CY)

3-0-0 3-0-0 3-0-0 3-0-0 3 3 3 3 6 Microbial systems for sustainable development

-

Microbial remediation and environmental biotechnology (level 4)

-

Microbes in food and sustainable agriculture (level 4)

-

Bioenergy (level 4) 3-0-0 3-0-0 3-0-0 3 3 3 7 Drug design and development

-

Principles of drug discovery (level 4)

-

Medicinal chemistry (level 4)

-

Viral infection and antiviral drug development (level 4) 3-0-0 3-0-0 3-0-0 3 3 3

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11. Specialization to be offered by the department

Table 7 Specialization and courses S.

No. Name of Specialization Specialization Core (8 credits) Specialization Elective (12 Credits) 1 Therapeutic

engineering and drug discovery

• Modern approaches of drug designing (3-0-0)

• Introduction to Precision Medicine (3-0-0)

• AI based drug discovery (2-0-0)

• Principles of drug discovery (3-0-0)

• Medicinal chemistry (3-0-0) • Viral infection and antiviral drug

development (3-0-0)

• Anti-microbial drug and drug resistance (2-0-0)

• Anticancer drug discovery and development (3-0-0)

• Modern approaches for immunotherapy (3-0-0)

• Novel Drug Delivery Systems (3-0-0)

• Theranostic Systems (3-0-0) • Industry collaborated project

4 credit (0-0-6) x 1 2 Microbial systems

engineering • Engineering Microbes (3-0-0) • Bioprocess Engineering and Fermentation (3-0-0)

• Mathematical modelling of microbes (1-0-2)

• Microbial Nanotechnology (3-0-0) • Metabolic Engineering for

biofuels (2-0-0)

• Microbial remediation and environmental biotechnology • Microbes in food and sustainable

agriculture • Bioenergy (3-0-0)

• Soil Microbiome & Microbial Technology (2-0-0)

• Biofilms: Bacterial communities (3-0-0)

• Gut microbiomes in health and diseases (3-0-0)

• Downstream processing (3-0-0) • Industry collaborated project 4 credit (0-0-6) x 1

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12. Curriculum of B.Tech. Bioengineering (Regular)

Table 8a. Curriculum of B.Tech in BB

Cat Course LTP CH N C GC Cat Course LTP CH NC GC I Semester II Semester IE Engineering Mechanics 2-1-0 3 - 3 IE Introduction to Electrical Engineering 3-0-2 5 - 4 IS Chemistry 3-0-0 3 - 3 IE Introduction to Computer Science 3-0-2 5 - 4 IS Physics 3-0-0 3 - 3 IE Introduction to Bioengineering 3-0-2 5 - 4 IS Chemistry Lab 0-0-2 2 - 1 IS Physics Lab 0-0-2 2 - 1 IS Mathematics I 3-1-0 4 - 4 IS Mathematics II 3-1-0 4 - 4 IE Engineering Visualization 0-0-2 2 - 1 IE Engineering Realization 0-0-2 1 - 1 NE Engineering Design I 0-0-2 2 1 - NE Engineering Design II 0-0-2 2 1 - NH Communicat ion Skill I 0-0-2 2 1 - N H Communication Skill II 0-0-2 2 1 - NH Social Connect and responsibiliti es I 0-0-1 1 0 . 5 - N H

Social Connect and responsibilities II 0-0-1 1 0.5 - NH Performing Arts I /Sports I 0-0-1 1 0 . 5 - N H Performing Arts II/Sports II 0-0-1 1 0.5 - Total 11-2-12 25 3 16 Total 12-1-14 27 3 17

III Semester IV Semester

LS Probability, statistics and stochastic process

3-1-0 4 - 4 IE Materials Science & Engineering F1: Materials selection, F2:Structure of materials, F3:Polymers 3 × (1-0-0) 3 - 3 IE Signals and Systems 3-1-0 4 - 4 IE PC PC PC PC Thermodynamics Data Structure and Algorithm

Concepts &

Dynamics: Molecular Cell Biology

The Human Immune System: Mechanisms to Detect, Defend and Attack 3-1-0 3-0-2 2-0-2 3-0-0 0-0-2 4 5 4 3 2 - - - - - 4 4 3 3 1 IE PC PC Introduction to Machine Learning Biochemistry Microbio logy 3-0-2 3-0-0 3-0-2 5 3 5 - - - 4 3 4

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Biochemistry Laboratory LS Nanoscience 3-0-0 3 - 3 IH Humanities I 3-0-0 3 - 3 NE Intro. To Profession 0-0-2 2 1 Total 18-2-6 26 1 22 Total 17-1-6 24 - 21 V Semester VI Semester PC Programme Compulsory Computatio nal and System Biology The Human Machine for Engineers: Quantitative Physiology Genetics and Gene Manipulatio n Biosensors 3-0-2 3-0-0 3-0-2 3-0-2 5 3 5 5 - - - - - 4 3 4 4 PC Programme Compulsory Introductory Omics Biomaterials Engineering Biophysics & Structural Biology Deep Learning Bioimaging 3-0-0 3-0-0 3-0-1 3-0-3 3-0-0 3 3 4 6 3 - - - - - 3 3 3.5 4.5 3 Program Elective -I 3-0-0 3 3 IH Humanities II

3-0-0 3 - 3 PE Program Elective -II 3-0-0 3 3 NH Professional Ethics I 0-1-0 1 1 - N H Professional Ethics II 0-1-0 1 1 - Total 18-1-6 25 1 21 Total 18-1-4 23 1 20

VII Semester VIII Semester

PP B. Tech. Project 0-0-6 6 - 3 IH Humanities IV 3-0-0 3 - 3 PE / OE Programme Elective-III &IV 6-0-0 6 - 6 PE / OE Programme Elective 5&6 6-0-0 6 - 6 Open Electives -I&II

6-0-0 6 6 Open Electives -III & IV 4-0-0 4 4 IH Humanities III 3-0-0 3 3 IS Environmen tal Science 2-0-0 2 - 2 Total 17-0-6 23 - 20 Total 13-0-0 13 - 13

Total of graded and Non-Graded Credit 9 150 Non-Graded Design Credits 6 -

Grand Total 1 5 165

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Distribution of courses in 7

th

& 8

th

Semester for specialization

VII Semester VIII Semester

PP B. Tech. Project 0-0-6 6 - 3 IH Humanities IV 3-0-0 3 - 3 PE / OE Programme Elective-III &IV 6-0-0 6 - 6 PE / OE Programme Elective 5&6 6-0-0 6 - 6 Open Electives

-I&II 6-0-0 6 6 Open Electives -III & IV 4-0-0 4 4 Specialization

Elective -I 3-0-0 3 3 Specialization Elective -II 3-0-0 3 3 IH Humanities III 3-0-0 3 - 3 Specialization

Project 0-0-8 8 4

IS Environmental Science

2-0-0 2 - 2

Total 20-0-6 26 - 23 Total 16-0-8 24 - 20 Total of graded and Non-Graded Credit 9 160

Non-Graded Design Credits 6 - Grand Total 15 175 Table 8b. Curriculum of B.Tech.in AI/CS/EE Engineering

Cat Course LTP C H NC GC Cat Course LTP CH NC GC I Semester II Semester IE Introduction to Electrical Engineering 3-0-2 5 - 4 IE Engineering Mechanics 2-1-0 3 - 3 IE Introduction to Computer Science 3-0-2 5 - 4 IS Chemistry 3-0-0 3 - 3 IE Introduction to Bioengineering 3-0-2 5 - 4 IS Physics 3-0-0 3 - 3 IS Chemistry Lab 0-0-2 2 - 1 IS Physics Lab 0-0-2 2 - 1 IS Mathematics I 3-1-0 4 - 4 IS Mathematics II 3-1-0 4 - 4 IE Engineering

Visualization 0-0-2 2 - 1 IE Engineering Realization 0-0-2 1 - 1 NE Engineering

Design I 0-0-2 2 1 - NE Engineering Design II 0-0-2 2 1 - NH Communication

Skill I 0-0-2 2 1 - NH Communication Skill II 0-0-2 2 1 - NH Social Connect

and

responsibilities I

0-0-1 1 0.

5 - NH Social Connect and responsibilities II 0-0-1 1 0. 5 - NH Performing Arts I /Sports I 0-0-1 1 0. 5 - N H Performing Arts II/Sports II 0-0-1 1 0. 5 - Total 12-1-14 27 3 17 Total 11-2-12 25 3 16

III Semester IV Semester

LS Programme linked Mathematics Core 3-1-0 4 - 4 IE Materials Science & Engineering 3 × 1-0-0 3 - 3 PC Data Structures

and Algorithms 3-0-2 IE Pattern Recognition and Machine

Learning

3-0-2 5 - 4

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IE Signals and Systems 3-1-0 4 - 4 Programme Compulsory 1. 6 × (1-0-0) 2. 4 × (0-0-1) 3. 2 × (0-1-0) 6-0-0 0-0-4 0-2-0 6 4 2 - - - 6 2 2 LS Programme linked Science Core 3-0-0 3 - 3 IH Humanities I 3-0-0 3 - 3 NE Intro. To Profession 0-0-2 2 1 Total 15-3-4 22 1 19 Total 15-2-6 23 - 20 V Semester VI Semester PC Programme Compulsory 1. 12× (1-0-0) 2. 8 × (0-0-1) 3. 2× (0-1-0) 12-0-0 0-0-8 0-2-0 12 8 2 - - - 12 4 2 PC Programme Compulsory 1. 12× (1-0-0) 2. 8× (0-0-1) 3. 2× (0-1-0) 12-0-0 0-0-8 0-2-0 12 8 2 - - - 12 4 2 IH Humanities II 3-0-0 3 - 3 PE Programme/Ope n Elective 3-0-0 3 3 NH Professional

Ethics I 0-1-0 1 - NH Professional Ethics II 0-1-0 1 -

Total 15-3-8 25 1 21 Total 15-3-8 25 1 21

VII Semester VIII Semester

PP B. Tech. Project 0-0-6 6 - 3 IH Humanities IV 3-0-0 3 - 3 PE / OE Programme/Ope n Electives 10-0-0 10 - 10 PE / OE Programme/Ope n Electives 15-0-0 15 - 15 IH Humanities III 3-0-0 3 - 3 IS Environmental Science 2-0-0 2 - 2 Total 15-0-6 21 - 18 Total 18-0-0 18 - 18 Total of graded and Non-Graded Credit 9 150

Non-Graded Design Credits 6 - Grand Total 15 165

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13. Curriculum of Double B.Tech. :B.Tech. Bioengineering and Engineering Science

Table 9. Programme structure of Double B.Tech.

Cat Course LTP CH N

C GC Cat Course LTP CH NC GC

I Semester II Semester

First two semesters same as Table 8a or 8 b 33 Graded and 6 non graded credits

III Semester IV Semester

ES Probability, Statistics, Stochastic Processes 3-1-0 4 - 4 IE Materials Science & Engineering 3 × 1-0-0 3 - 3

ES Morden Physics 3-0-0 3 - 3 ES Embedded

Systems and IoT 3-0-2 5 - 4 IE Thermodynamics 3-1-0 4 - 4 IE Pattern

Recognition and Machine Learning

3-0-2 5 - 4

ES Data Structures and

Algorithms 3-0-2 5 - 4 ES Design of Experiments 3-0-0 3 - 3 IE Signals and Systems 3-1-0 4 - 4 ES Control Systems 3-0-2 5 - 4 NE Intro. To Profession 0-0-2 2 1 IH Humanities I 3-0-0 3 - 3

Total 15-3-4 22 1 19 Total 18-0-6 24 - 21 V Semester VI Semester PC IH Programme Compulsory Biochemistry Microbiology Computational and System Biology

Genetics and Gene Manipulation Biosensors Humanities II 3-0-0 3-0-2 3-0-2 3-0-2 3-0-2 3-0-0 3 5 5 5 5 3 - - - - - - 3 4 4 4 4 3 PC Programme Compulsory Concepts & Dynamics: Molecular Cell Biology Biochemistry Laboratory Introductory Omics Deep Learning Bioimaging The Human Immune System: Mechanisms to Detect, Defend and Attack 2-0-2 0-0-2 3-0-0 3-0-3 3-0-0 3-0-0 4 2 3 6 3 3 - - - - - - 3 1 3 4.5 3 3 Biophysics & Structural Biology 3-0-1 4 - 3.5 NH Professional Ethics I 0-1-0 1 - NH Professional Ethics II 0-1-0 1 - Total 18-1-8 26 1 22 Total 17-1-8 25 1 21

VII Semester VIII Semester

PP B. Tech. Project 0-0-6 6 - 3 PC Biomaterials Engineering

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PE / ES Programme/Engi neering Science Electives 15-0-0 15 - 15 PC Programme Compulsory The Human Machine for Engineers: Quantitative Physiology 3-0-0 3 - - 3 IH Humanities III 3-0-0 3 - 3 PE/ OE Programme/Engine ering Science Electives 15-0-0 15 - 15 IS Environmental Science 2-0-0 2 - 2 Total 20-0-6 26 - 23.0 Total 21-0-0 21 - 21 Total of graded and Non-Graded Credit 9 160

Non-Graded Design Credits 6 - Grand Total 15 175 Note: ES are proposed Engineering Science compulsory courses

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14. Detailed Course Content of Programme Compulsory Courses

Title Biochemistry Number

Department Biosciences & Bioengineering L-T-P [C] 3–0–0 [3]

Offered for B. Tech Type Compulsory

Prerequisite None

Objectives

The Instructor will:

Introduce basic chemical properties of biomolecules and principles governing chemical properties of cell.

Learning Outcomes

The students will have the ability to:

Understand the structure-function relationship of biomolecules in living system.

Contents

Chemistry of Lipids [5 Lectures]: Classes of Lipids and their structure; Membrane Lipids and their properties; Bio

membrane organization; Sterols; Membrane Transport

Chemistry of Amino Acids [5 Lectures]: Amino acid structure and properties; Peptide bond; acid-base chemistry

of amino acids; isoelectric point

Chemistry of Proteins [5 Lectures]: Protein structure and its importance; Enzymes; Michaelis-Menten kinetics;

Enzyme inhibition

Nucleic acid chemistry [5 Lectures]: Nucleotides; DNA; RNA; Types of RNA

Properties of Carbohydrates [4 Lectures]: Aldoses, Ketoses; Epimers; Mutarotation; Glycosidic bond

Carbohydrates Chemistry [5 Lectures]: Common polysaccharides; Reducing & Non reducing sugars;

Glycoproteins

Bioenergetics [5 Lectures]: Catabolism; Anabolism; Energy Coupling; High energy bonds formation and

dissociation

Metabolic pathways [5 Lectures]: Glycolysis; TCA, Electron Transport Chain, Calvin cycle, Reverse TCA

Active learning component [3 Lectures]: Flipped classroom (group presentations), debates, case studies on applied

biochemistry, group discussions, think-pair-share

Text Book

D. L. Nelson and M. N. Cox, Lehninger Principles of Biochemistry, WH Freeman, (2012), Sixth Edition.

Reference Book

D. Voet, C. W. Pratt and J. G. Voet, Principles of Biochemistry, Wiley (2012), Fourth Edition.

Self-Learning Material

S Dasgupta, Biochemistry I, NPTEL Course Material, Indian Institute of Technology Kharagpur, http://nptel.ac.in/courses/102105034/

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Title Microbiology Number

Department Bioscience & Bioengineering L-T-P [C] 3–0–2 [4]

Offered for B.Tech Type Compulsory

Prerequisite None

Objectives

1. Give students foundational knowledge on the microbial world

2. Provide context as to how these microbes play an essential role in human health and environment

The students are expected to have the ability to:

1. Understand the biology of microbes and how they impact life on earth 2. Explore unique structure-function relationships in microbes

3. Analyse the diversity in microbial metabolism and its adaptability to environmental changes

Laboratory Experiments

Biosafety, Microscopic examination of microbial world - Staining; Preparation and sterilization of microbial growth media, Microbial motility and Chemotaxis; Cultivating microbes by streak plate and pour plate method. Enumeration of microbes by turbidometry; Microbial enumeration by plate count; Effect of pH and temperature on microbial growth; Safely discarding microbial cultures

Textbook

1. R. Y. Stanier, General Microbiology, Macmillan (1999), 5th_edition.

2. M. Pelczar, A. Chen, A. Krieg, Microbiology, Tata McGraw Hill Education (2001), 5th_edition.

3. R. M. Atlas, R. Bartha Microbial Ecology: Fundamentals and applications, Pearson, (1997), 4th_edition.

Reference Books

1. Brock, et al., Biology of Microorganisms, Benjamin Cummings (2012), 13th_edition

2. D. L. Nelson and M. N. Cox, Lehninger Principles of Biochemistry, WH Freeman, (2012), Sixth Edition. 3. P. Harley, Klein’s Microbiology, McGraw Hill Higher Education, (2008), 7th edition,

Online Course Material

David Schauer, and Edward DeLong. 20.106J Systems Microbiology. Fall 2006. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA

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Title The Human Immune System: Mechanisms to Detect,

Defend and Attack Number

Department Biosciences & Bioengineering L-T-P [C] 3-0-0 [3]

Prerequisite None

Objectives

1. Provide an overview of the human immune system and its components

2. Emphasize immune responses in context of bacterial, viral and parasitic infections.

The students are expected to have the ability to: 1. Evaluate applications of immunology in industry

2. Apply their knowledge for design of immunological experiments

Textbook

1. K. Murphy, P. Travers, M. Walport, C. Janeway, Janeway’s Immunobiology. New York: Garland Science (2012) 8th_edition.

Reference Books

1. T. J. Kindt, R. A. Goldsby, B. A. Osborne, J. Kuby. Kuby Immunology. New York: W.H. Freeman (2002), First edition.

2. J. Brostoff, J. K. Seaddin, D. Male, I. M. Roitt, Clinical Immunology. London: Gower Medical Pub (2002), First edition.

Self-Learning Materials

Cellular and molecular immunology, Fall 2005, MIT OpenCourseWare Massachusetts Institute of Technology, https://ocw.mit.edu. License: Creative Commons BY-NC-SA

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Title Concepts and dynamics: molecular cell

biology Number

Prerequisite None

Objectives

The instructor will:

1. Offer both basic and advance concepts in cellular and molecular biology. The focus of the course is to provide basic understanding of functional machineries of cells.

2. Apprise the students about the dynamics of cellular processes and the regulatory mechanisms involved.

Learning Outcomes

The students are expected to:

Have the ability to understand the structure and function of cells as a fundamental unit of life.

Contents

Cell organelles and cellular signalling [5 Lectures]: Structure and function of cellular organelles

Cellular architecture [5 Lectures]: Cytoplasmic and nuclear compartment, basic protein structure and cellular

signalling

Cell division and proliferation [5 Lectures]: Biological principles of mitosis and meiosis; difference of cell division among prokaryotes and eukaryotes and cell cycle regulation in health and diseases.

Mechanisms of cell death & diseases [5 Lectures]: phases and significance linked with apoptosis, morphological

and biochemical changes associated with apoptotic cells.

Regulation of gene expression [4 Lectures]: DNA replication, prokaryotic & eukaryotic transcription prokaryotic

transcription; transcription unit and TATA binding proteins, translation.

Cellular quality control mechanisms [4 Lectures]: cellular stress conditions and their effects; protein quality

control mechanisms and nucleic acid quality control mechanism.

Laboratory experiments: bacterial transformation, mammalian cells transfections; DNA gel electrophoresis; cell death assays; localization of proteins in different cellular compartments; DNA ligation and digestion; animal cell culture and immunocytochemistry.

Textbook

1. B. Alberts., Molecular Biology of the cell, Garland Science, 2014, 6th_Edition

2. G. Karp and N. L Pruitt., Cell and Molecular Biology, John Wiley and Sons, 2016, 8th_Edition

Reference Book

1. L. Benjamin, Gene IX, Jones and Barlett Publishers, 2007, 9th_Edition

2. J.D. Watson, Molecular Biology of the Gene, Benjamin Cummings, 2007, 6th_Edition

Self-Learning Material

NPTEL Lectures: on Molecular Cell Biology, Devarajan Karunagaran, IIT Madras http://nptel.ac.in/syllabus/102106025/

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Title Biochemistry Laboratory Number

Prerequisite Biochemistry (PC 3rd₎

Objectives

Give hands-on training on standard biochemical techniques and its applications.

Learning Outcomes

The students will be able to:

Perform and implement biochemical techniques in research and industrial applications.

Contents

Identification of biomolecules in samples: proteins, carbohydrates and lipids

Protein isolation and purification: salting out, chromatography (ion-exchange and affinity), SDS-PAGE

Characterization of proteins using spectroscopic techniques: absorbance, fluorescence and secondary structure

determination

Protein estimation by different methods: BCA, Bradford and Lowry

Identification and quantification of nucleic acids: absorbance and gel based methods

Text Book

D. K. Geetha Practical Biochemistry, Jaypee Brothers Medical Publishers (2016) 2nd_Edition.

Elizabeth Taylor. 5.36 Biochemistry Laboratory. Spring 2009. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu.

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Course Title Computational and Systems Biology Course No. BBL3XXX0 Department Bioscience and Bioengineering Structure (L-T-P-C) 3-0-2 [4]

Offered for B.Tech. Type Program Compulsory (PC)

Pre-requisite Basic understanding of molecular biology and computation

Objectives

1. To train the students in the interdisciplinary areas on the interface of biology and computation. 2. To provide fundamental understanding of methods in computational biology along with hand on

training.

1. Application of computational methods for modelling biological systems. 2. Ability to model and infer from biological models.

Course Content

Genome and Sequences [Lectures 2]: Sources of information of biological origin, gene and protein sequences,

sequence homology and its biological significance (2 lectures)

Building biological databases with SQL [Lectures 6] : Common database types, relational database design (3

lectures), database access using SQL (2 lectures), biological databases (1 lecture)

Sequence Alignment [Lectures 10]: Need for aligning biological sequences, Smith-Waterman algorithm,

Needleman-Wunsch algorithm (4 lecture), Multiple Sequence Alignment (2 lecture) , Phylogeny (2 lecture), Applications, BLAST (2 lecture)

Gene and promoter prediction [Lectures 4]: Gene prediction, promoter and regulatory element prediction Protein Structure Prediction [Lectures 6]: Protein folding (1 lecture), Ab initio and knowledge-based prediction

of structures, Force fields (3 lectures), Homology modelling (2 lectures)

Introduction to Mathematical Modelling [2 lecture]: Introduction to Modelling, why model biological systems?,

examples of models, the modelling process, scope/assumptions, types of models

Introduction to Static Networks [12 lectures]: Representation of Biological Networks (1 lecture), Introduction to

Network Biology (3 lectures), Network Topology, Power-law Networks/Network Perturbations (3 lectures), Community Detection / Network Motifs (3 lectures), Reconstruction of Gene networks (2 lectures)

Laboratory [10-12 Sessions]

Database searches and data retrieval, Database creation and data retrieval using MySQL, Writing code for translation of nucleic acid sequence to protein sequence, Writing code for dynamic programming and performing global alignment, Pairwise sequence alignment: BLAST, Multiple Sequence alignment: CLUSTAL OMEGA, Gene prediction tools (Glimmer, GeneMark) Visualisation and analysis of 3D-structures of proteins and protein-ligand interactions using graphics tool (RasMol), Homology modelling using SWISS-MODEL, Network Biology (Cytoscape), Network Biology (Topologies), Motif and module detection, Parameters of network (Cytoscape),, Network Perturbations, reconstruction of gene regulatory network

Text Book

D. Mount, Bioinformatics: Sequence and Genome Analysis, Cold Spring Harbor laboratory Press (2004), Second Edition.

Reference Books

1. R. Durbin, S. Eddy, A. Krogh, G. Mitchison, Biological Sequence Analysis, Cambridge University Press (1998) First Edition.

2. C. Branden, J. Tooze, Introduction to Protein Structure, Garland Science (1999) Second Edition.

3. P Baldi, S Brunak, Bioinformatics: The Machine Learning Approach, Bradford Publishers (2001) Second Edition.

Multimedia Content

1. NPTEL course link: Bioanalytical Techniques And Bioinformatics (http://nptel.ac.in/courses/102103044/) 2. Video lectures on Foundation of Computational and Systems Biology, MIT Open Courseware, (https://ocw.mit.edu/courses/biology/7-91j-foundations-of-computational-and-systems-biology-spring-2014/index.htm).

3. Lecture Notes for Introduction to Computational Molecular Biology and Genomics by Prof. Mona Singh, (https://www.cs.princeton.edu/~mona/computational_biology_notes.html).

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Title The Human Machine for Engineers:

Quantitative Physiology Number

Department Bioscience and Bioengineering L-T-P [C] 3–0–0 [3]

Offered for B.Tech Type Compulsory

Prerequisite None

Objectives

1. Provide an understanding of the hierarchical organization of chemical and electrical signals and control mechanisms for energy, mechanics, flow and transport.

2. Provide an understanding of the workings of the human body in context of engineering principles so as to develop an interdisciplinary outlook to biological as well as engineering problem-solving.

1. Understand and analyse basic human physiology from an quantitative perspective

2. Imagine engineering solutions that can solve biological problems and/or get inspired by biology to solve engineering problems.

Text Books

1. J. Feher Quantitative Human Physiology, Academic Press, 2nd_{Edition (2016).}

2. K. E. Barrett, S. M. Barman, Ganong’s Review of Medical Physiology, McGraw Hill Education, 26th_Edition, (2019).

Reference Books

1. E.N. Marieb Human Anatomy and Physiology, Pearson Education (2006), 6th_Edition. 2. W. F. Boron, E. L. Boulpaep Medical Physiology, Elsevier (2017) 3rd_Edition.

Self-Learning Material

1. Dennis Freeman, 6-021j Quantitative Physiology: Cells and Tissues, Fall 2004, MIT OpenCourseWare Massachusetts Institute of Technology, https://ocw.mit.edu. License: Creative Commons BY-NC-SA 2. Venegas, J, Mark, F. Quantitative Physiology: Organ Transport Systems, MIT OpenCourseWare

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Title Biophysics and Structural Biology Number

Department Bioscience and Bioengineering L-T-P [C] 3–0–1 [3.5]

Prerequisite

Objectives

The instructor will provide

1. In-depth understanding of three dimensional structure of bio-macromolecules and macromolecular assemblies governing the cellular life.

2. Introductory idea of the state of the art tools and techniques in understanding the interactions of biological molecules.

After completion of the course the students are expected to have the ability to -

1. Conceptualize the basic principles of macromolecular structural assembles and their implications in the regulation of biological phenomena.

2. Understand the basic principles of modern day techniques of structural biology and their applications in academia-industrial settings.

Biophysics of macromolecular interactions [14 Lectures]: Physical forces in macromolecular interactions (2

lectures), protein -protein and protein -nucleic acid interactions (3 lectures), structure of heme, myoglobin and haemoglobin, oxygen binding mechanism (3 lectures), Bohr effect, Energetics of active transport (3 lectures), Principles of spectroscopic methods for studying macromolecular interaction (3 lectures).

Lab components

1. Introduction to Macromolecular Structure

2. Retrieving biochemical information from protein primary structure. 3. Prediction of protein 3D structure model from amino acid sequence 4.Validation of protein 3D structure model

5. Analysis of protein 3D structure - a. Overall structure and enzyme active site b. Enzyme allosteric site

c. Enzyme substrate specificity

d. Enzyme inhibition by small molecule/peptide 6. Protein -small molecule docking and analysis 7. Protein-protein docking and analysis

8. Protein-DNA docking and analysis

9. Analysis of the effect of mutation(s) in protein interactions

Text Books

1. A. M. Pherson, Introduction to Macromolecular Crystallography, Wiley-Blackwell (2009), 2nd Edition. 2. W. Bialek, Biophysics – Searching for Principles, Princeton University Press (2012).

3. R. Glaser, Biophysics: An Introduction, Springer (2012) 2nd_edition.

Reference Books

1. D. Voet, C. W. Pratt and J. G. Voet, Principles of Biochemistry, Wiley (2012), Fourth Edition.

1.https://ocw.mit.edu/courses/biological-engineering/20-430j-fields-forces-and-flows-in-biological-systems-fall-2015/

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Course Title Genetics and Gene Manipulation Number

Department Bioscience and Bioengineering L-T-P [C] 3-0-2 [4]

Pre-requisite None

Objectives

1. Provide an overview of the principles of heredity and gene manipulation

2. Highlight how gene manipulation can be applied to engineer simple and complex life forms and safety considerations associated with genetic engineering

1. Choose the best method to manipulate DNA for genetic engineering applications 2. Engineer simple biological systems for biotechnological applications

3. Practise safety and ethical considerations while manipulating and engineering biological systems

crossovers and recombination (6 lectures), genetic drift, effect measures (6 lectures), study designs, Hardy-Weinberg law, linkage disequilibrium, linkage and association analysis, principles of inheritance, simple and complex diseases, heritability estimation, genetic markers, DNA fingerprinting (6 lectures)

Gene Manipulation [12 Lectures]: Polymerase Chain Reaction (2 lectures), DNA modifying enzymes (1 lecture),

strategies for gene cloning (3 lectures), gene editing (1 lecture), vectors, selection & screening (2 lectures), sequencing DNA (1 lecture), heterologous expression of genes (2 lectures)

Genetic Engineering [6 Lectures]: Gene transfer to animal cells & transgenic animals (2 lectures), gene transfer to

plant cells & transgenic plants (2 lectures), genetically modified organisms (2 lectures)

Applications of Genetic Engineering [4 Lectures]: Production of important metabolites (1 lecture), introducing new

traits, improving existing traits (1 lecture), gene therapy, development of model systems, animal cloning (2 lectures)

Ethical & Safety Considerations [2 Lectures]: Biosafety considerations for recombinant DNA research (1 lecture),

Ethical considerations for Genetic Engineering (1 lecture)

Laboratory Experiments (12 exercises)

Cloning strategies; Transformation, Selection & Screening; Clone confirmation & Sequencing of cloned DNA; Directional cloning; Heterologous protein expression; Site directed mutagenesis

Text Books

1. S. B. Primrose, and R. M. Twyman, Principles of Gene Manipulation & Genomics, Blackwell Publishing (2006), 7th Edition.

2. N. M. Laird, and C. Lange, The Fundamentals of Modern Statistical Genetics, Springer: New York (2011), First edition.

Reference Books

1. M. Nagarajan, Ed. Metagenomics: Perspectives, Methods, and Applications, Elsevier (2017) 1st_Edition, 2. D. P. Snustad, M. J. Simmons, Principles of Genetics, John Wiley and Sons (2011), 6th Edition.

1. https://nptel.ac.in/courses/102/103/102103013/

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Title Introductory Omics Number BBL4XX0

Offered for B.Tech. Type Compulsory

Prerequisite None

Objectives

1. Introduce the organization of a genome and highlight the complexity of the encoded proteome and resulting metabolome

2. Describe methods to access the genome, proteome and metabolome for specific applications 3. Highlight applications of genomics, proteomics and metabolomics in biological research

1. Sequence and analyse the genome of a simple organism to understand its functioning

2. Appreciate the usage of proteomics approaches to obtain a global picture of cellular activities 3. Understand the metabolic complexity of simple organisms from the perspective of their genome and

proteome

Text Book

S. B. Primrose and R. M. Twyman Principles of Gene Manipulation & Genomics, Blackwell Publishing (2006) 7th_Edition.

Reference Books

1. A. M. Lesk, Introduction to Genomics, Oxford University Press (2017), 3rd_Edition. 2. R. Twyman, Principles of Proteomics, CRC Press (2013), 2nd_Edition.

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Title Biomaterials Engineering Number

Department Bioscience and Bioengineering L-T-P [C] 3–0–0 [3]

Prerequisite None

Objectives

1. Provide an insight on the fundamental concepts of biomaterials engineering.

2. Give an overview of techniques for characterizations of different types of biomaterials for various applications.

1. Analyze the suitability of the material to be used as a biomaterial. 2. Compare the performance of different biomaterials.

2. Design a strategy for modification of biomaterials for a specific application.

Contents

Fundamental of Biomaterials [14 Lectures]: Introduction to biomaterials (2 lectures), types of biomaterials (1

lectures), processing of biomaterials (4 lectures), surface properties and surface modification of biomaterials (3 lectures), physicochemical characterization of biomaterials (4 lectures). (offered by MM department)

Biological properties of biomaterials [14 Lectures]: Concepts of biocompatibility, immune-compatibility,

hemocompatibility and biodegradability (5 lectures), Bioconjugations, Biomineralization (4 lectures), Biological characterization of biomaterials (5 lectures) (offered by BSBE)

Applications of Biomaterials [14 Lectures]: Biomimetic and stealth biomaterials (3 lectures), types and

applications of implants (4 lectures), biomaterials for drug delivery systems (3 lectures), biomaterials for tissue engineering (3 lectures), regulatory affairs (1 lecture) (offered by BSBE)

Text Books

B. Bikramjit, Biomaterials Science and Tissue Engineering, Cambridge University Press (2017), First edition.

Reference Books

W. R. Wagner, Shelly E. Sakiyama-Elbert, Guigen Zhang, Michael J. Yaszemski, Biomaterials Science: An Introduction to Materials in Medicine, Academic Press Inc (2020), 4th edition.

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15. Detailed Course Content of Programme Elective Courses

Omics

S. No Title of the course Offered by

1 Microbiomes and Metagenomics BSBE

2 Computational Methods for Multi-omics BSBE

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Title Microbiomes and Metagenomics Number BBL4XX0

Offered for B.Tech Type Elective

Prerequisite

Objectives

1. Introduce microbial communities that are ubiquitous and are functionally adapted to specific environments

2. Outline methods to understand microbial community structure in a given environment 3. Describe strategies to access the genomic diversity specific to these microbial communities

Learning Outcomes

1. Unravel microbial communities associated with specific environments using culture-dependent / independent methods

2. Access metagenomes associated with unique environments to bioprospect enzymes, metabolites and bioactive compounds

Contents

Fractal 1. Quantitative ecology of Microbial communities [14 Lectures]: Development of microbial communities (2

lectures), selection and succession, diversity and stability of communities (3 lectures), indices for diversity (2 lectures), structure and function of some natural microbial communities (2 lectures), accessing the microbiome: from sample collection to detection of microbial populations, counting microbes (3 lectures), measuring microbial biomass and metabolism (2 lectures)

Fractal 2. The current standard in microbiome profiling [14 Lectures]: Extraction of environmental DNA (2

lectures), PCR considerations in microbiome research (2 lectures), multiplexing samples, next generation sequencing primer (2 lectures), exploiting NGS methods for microbiome profiling (2 lectures), data analyses (4 lectures), assessment of community diversity (2 lectures)

Fractal 3. Metagenome sequencing [14 Lectures]: Metagenome library construction and sequencing (2 lectures),

metagenome amplification, shotgun metagenome sequencing (3 lectures), single-cell metagenomics (2 lectures), predicting genes and gene function from metagenomes (2 lectures), metabolic reconstruction of microbial communities (2 lectures), bioprospecting from metagenomes (3 lectures)

Text Books

1. R. Atlas, R. Bartha, Microbial Ecology: Fundamentals and Applications, Pearson (1998), 4th_edition.

2. J. Izard, M. Rivera, Eds. Metagenomics for Microbiology, Elsevier (2015), First edition.

Reference Books

1. M. Nagarajan, Ed. Metagenomics: Perspectives, Methods, and Applications, Elsevier (2017), 1st_Edition. 2. Research articles, Case reports & Review articles as provided by the Instructor

Self-Learning Material

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Title Computational Methods for

Multi-omics Number BBL4XX0

Offered for B.Tech Type Programme Elective (PE)

Prerequisite Introductory Omics

Objectives

1. Introduce to basic knowledge of computational and statistical methods in omics data analysis

2. Highlight how multi-omics data is to be preprocessed, assessed for integrity, analyzed and interpreted appropriately

Learning Outcomes

The students are expected to have the ability to:

1. Identify key methods for analysis and integration of omics data based on a given dataset 2. Efficiently analyze large scale multi-omics data sets

3. Make biological inference from the analyzed data

Contents

Fractal 1: Basics of Multi-omics Analysis (14 lectures)

Genome first and phenome first approaches, biological networks and pathways (4 lectures), multi-omics data types and repositories, multi-omics data examples, biological interpretation (4 lectures); homogeneity and heterogeneity issues, batch effect correction, normalization and transformation (4 lectures); processing of high-throughput multi-omics data sets (2 lectures)

Fractal 2: Horizontal Multi-omics Integration (14 lectures)

Horizontal integration scheme, single-level omics data, meta-analysis methods (4 lectures); integration methods for multiple biological networks, integration of genetically regulated gene expression data (4 lectures); correlation motif model, ChIP-X data integration, analysis of allele-specific binding in ChIP-Seq (3 lectures); illustrative case-studies (3 lectures)

Fractal 3: Vertical Multi-omics Integration (14 lectures)

Vertical integration schemes including parallel integration and hierarchical integration (3 lectures); clustering methods, latent variable approach (4 lectures); Bayesian methods, network-based methods, HotNet algorithm (4 lectures); illustrative case-studies (3 lectures)

Laboratory Experiments (14 classes)

perform multi-omics integration for cancer TCGA data sets (4 lectures); analyze the complex structure of repeated measurements from different biological assays using open access data sets (4 lectures); develop a meta-analysis approach for integrating data on blood lipid levels (3 lectures); apply visualization approaches for the multi-omics analyses and biological interpretation (3 lectures)

Textbook

1. G. Tseng, D. Ghosh, X. J. Zhou, Integrating Omics Data. Cambridge University press (2015), First edition.

Reference Books

1. A. Vlahou, F. Magni, H. Mischak, J. Zoidakis, Integration of Omics Approaches and Systems Biology for clinical applications. Wiley (2018), First edition.

Self-Learning Material

1. George Michailidis, University of Michigan, Data-driven Approaches and Multi-omics Integration, https://www.youtube.com/watch?v=OoBvkRpBqf0

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Title Microarray Data Analysis Course No. BB4XX0

Department Bioscience and Bioengineering Structure (L-T-P-C) 3-0-0 [3]

Offered for B.Tech. Type Elective

Pre-requisite Basic understanding of molecular biology and computation

Objective

1. Training students to analyze microarray technology/RNA sequencing gene expression data.

2. To be knowledgeable about high dimensional biology data analysis. The course will help to minimize a major bottleneck in the utilization of these data.

3. To familiarize the students with the use of advanced tools and methodologies for analyzing microarray/RNA seq expression data

4. Assignments will help them to practice and learn about the tools required in the microarray data analysis

Learning Outcomes

1. Be able to understand the structure of the data, the statistical procedur